Williams felt it was a formality, designating pitcher Jeff Marquez for assignment upon the return from the DL of Mark Teahenon Sunday and settling him back into the rotation at AAA Charlotte, where he had compiled a sub-4.00 ERA for the Knights. Then New York Yankees GM Brian Cashman stepped in to muck up that plan.

“No I didn’t,” Williams said when asked whether he thought there would be any problem with holding on to Marquez. “Ask Brian Cashman. Ask Brian Cashman. He got a message [from me]. But that’s the risk you take.” … “The truth of the matter is we would have tried to re-sign [Marquez] and put him back in uniform today with Jake’s injury, Williams said, before adding with a smile, “but the Yankees have a greater need right now.”

You should be mad for trading Nick Swisher to the Yankees for peanuts Kenny.

May 8, 2011

Yet when asked directly about whether certain moves over the past few years didn’t make this team better, Williams again wouldn’t grade on a pass-fail sort of system. It’s not as simple as judging on statistics alone.

Take the 2008 trade of Nick Swisher — who has found a home roaming the outfield at Yankee Stadium — which brought the White Sox two Minor League pitchers in return. Plain and simple, Swisher didn’t fit with the White Sox.

“A lot of times, people don’t necessarily understand it’s not always about the talent you get back,” Williams said. “Sometimes it’s about the monetary relief you get, so that it will allow you to go out and get somebody else that is a better fit. It’s not always about the production of a player or the talent of a player.

Righthander Fautino de los Santos has rarely been heard from since blowing through two Class A stops in the White Sox system in 2007, going a combined 10-5, 2.65 and earning a trip to the Futures Game. Traded to the A’s in the Nick Swisher deal after that season, de los Santos logged just 35 innings over the last two years after needing Tommy John surgery in 2008. After a prolonged rehab period, de los Santos finally got back on the mound for high Class A Stockton last night, making his 2010 debut by coming out of the bullpen in the seventh inning of the Ports’ game against Modesto. He didn’t take long to knock off any rust, retiring all six hitters he faced and striking out two of them.

A principle component analysis depends greatly on the variables fed into it. For hitters, I used the singles, doubles, triples, homers, walks, and strikeouts per plate appearance as the input variables. While I could do that here, I thought I would use variables over which the pitcher had more direct control. Using Fangraphs pitch data, I used the following: % of Fastballs Thrown (including cutters), % of Sliders, % of Changeups, Velocity of Fastball, Ground Ball%, Walks per PA, and Strikeouts per PA. I thought about using Hits per PA, and HR per PA, but since those are largely a function of luck and I didn’t want to measure that, I decided to leave them out. Like before, each variable was normalized before putting it into the model.

For hitters I was uncertain of what to expect, however for pitchers I had a fairly good idea. I expected that the two groupings of pitchers would be between power pitchers and control pitchers. However, I wasn’t exactly sure how it would break it down. Running the analysis, the factor loadings for the first principle component were as follows: …

For those unfamiliar with the type analysis, the point of it is to reduce a large number of potentially correlated variables down to a few key underlying factors that explain the variables. The researcher feeds the computer a bunch of records (in the this case, players) and several key variables (in this case, their statistics), The computer, blind to what those variables actually mean, spits out a set of underlying factors which explain the “true” underlying causes for the variables in question. It does this by maximizing the variability between the players. It’s then up to the researcher to interpret what each factor represents. In this case, I’m looking for the one underlying factor that best describes a player.

In the baseball world, I wondered what one underlying factor best determined a player’s statistics. Normally, this type of analysis would be done on many more variables, but I wanted to see what it would pick out from players’ basic, non-team influenced statistics: 1B, 2B, 3B, HR, BB, K.

Mark Liptak: What does Kenny look at when he figures out what to do this off season?

Mark Gonzales: “As I figured it out the Sox have 10 players going to make 71.5 million next season and that includes Dayan Viciedo who I think will be with the team at some point next year. It wouldn’t surprise me in the least if this off season Kenny moved some guys to give him more dollars to work with.”

“Kenny remember, and this is important, is a man of action, not reaction. It’ll be interesting to see how patient Kenny will be especially if the free agent market again tilts in favor of the buyer. I look for Kenny to aggressively improve the team through trades but he’ll also keep in mind some possible free agent bargains that could be out there.” …

A lot more at the link: Swisher, Walker, BA, Ozzie, Kenny, Vazquez, Betemit, Reinsdorf, Byddy Bell and much more.

October 9, 2009

Swisher’s rate of HR’s, K’s SB’s, line drives, fly balls, pop ups and grounders suggested that his BABIP should have been closer to the .300 range in 2008. That would obviously change his line dramatically. Even if those extra hits were all singles, Swisher’s triple-slash would rise from a mild .219/.332/.410 to .268/.381/.459. With the Bronx Bombers in 2009, Swisher mashed to the tune of .249/.371/.498 in 607 PA, good for a career-best .375 wOBA. His BABIP did not return to the .300 range (he finished at .277), but that BABIP rebound and a boost in power (.249 ISO) made Swisher one of the best off-season pickups. His patience and pop, coupled with average D, produced a 3.7 WAR season. Swisher is never going to have a shiny batting average, but his stout secondary skills (walks and power) make him an underrated contributor. …

September 25, 2009

He isn’t very good. Ignore the numbers and his ability to play a few positions, and what you have is a player that likes to swing for the fences and look for walks. The result is a lot of ugly swings at bad pitches and a lot of looks at good ones.

Well, give me a .251/.368/.495/.863 batting line with a 89/120 BB/K ratio at $5.3M and you can swing from your ass and I couldn’t care less.

September 12, 2009

A year ago, Swisher was one of the unluckiest players in baseball. His line drive rate in 2008 was a career-high 20.9 percent. Based on that figure, his expected batting average for balls in play was .329, which would have been a just reward for hitting the ball hard. But instead, even though he pounded the baseball, Swisher’s BABIP was a criminally low .251, a number that can be attributed to lots of terrible luck. So, despite the fact that his walk rates and strikeout rates were roughly the same in 2008 as they were compared to the rest of his career, Swisher’s productivity went into the tank, thus earning himself a one-way ticket out of the Windy City. Flash forward to Tuesday night. After swatting a pair of homers against the Rays, Swisher is hitting .254/.378/.506, defying even the most optimistic projections. His 26 homers are the second highest total of his career. … In 2008, Swisher had a career-low .325 weighted on-base average, a statistic that attempts to measure a player’s overall offensive production. So far in 2009, Swisher’s wOBA is .374, a career high.